Biology subjects

Rigoux, L.

Publications and source records attributed to Rigoux, L..

6 recordsLinked to original sources

bioRxiv2026

Motor learning adapts to effort-dependent uncertainty

Adaptive behaviour depends on continuously updating motor control when action outcomes differ from expectations. Because action execution and sensory feedback are noisy, the value of an error depends on how reliably it reflects the consequences of an action. Most studies have manipulated the reliability of sensory feedback or action outcomes rather than uncertainty generated by the action itself. Here we show that motor adaptation is calibrated to effort-dependent uncertainty arising during action generation. Using a force-based motor adaptation paradigm, we demonstrate that greater effort progressively increased uncertainty in action execution and proprioceptive feedback, with corresponding changes in adaptation rate that closely matched normative predictions. Reward enhanced adaptation by improving proprioceptive precision rather than directly changing adaptation rate. Supporting this framework, patients with major depressive disorder exhibited elevated execution and proprioceptive uncertainty, impaired reward-dependent improvement in proprioceptive precision, and slower motor adaptation. These findings establish intrinsic uncertainty as a general determinant of adaptive behaviour, linking action generation, sensory evaluation, and motivation.

neuroscience↗

bioRxiv2026

Metabolic state and energy reserve dynamically shape human decision-making

Animals continuously adapt their behaviour to changing physiological needs through flexible regulation of behavioural control. However, how the energetic state shapes the distinct components of this adaptive control in humans remains poorly understood. Here, we tested how fasting-induced energy deficits and stored energy reserves jointly regulate inhibitory control and incentive motivation in healthy participants. Fasting selectively increased impulsivity for food rewards, an effect attenuated by body fat percentage. In contrast, fasting increased effort expenditure across both food and monetary rewards, revealing a domain-general increase in motivation best explained by relative energy deficit--the ratio of energy expended during fasting to stored energy reserves. Neither effect was explained by changes in subjective reward valuation. Although self-report questionnaires captured stable behavioural tendencies, they failed to account for state-dependent behavioural variation. Together, these findings show that inhibitory control and motivation are governed by distinct metabolic principles operating across different timescales, revealing that adaptive behavioural control depends on the energetic significance of metabolic state rather than on fasting alone.

neuroscience↗

bioRxiv2026

A computational neuroimaging account of impulsive premature decision-making

Impulsivity is a multidimensional construct with distinct implications for the pathophysiology and treatment of various neuropsychiatric conditions, including substance use disorders, behavioural addictions, attention deficit hyperactivity disorder, psychosis, and personality disorders. One proposed behavioural subtype, premature responding impulsivity (PRI), appears to be influenced by neuromodulatory pathways frequently implicated in these disorders, in particular dopamine neurotransmission, known for its role in contingency learning. Still, the neurobiological basis of PRI in humans remains insufficiently understood. Here, we theorize that PRI reflects the brains capacity to adapt to environmental uncertainty. To test this hypothesis, twenty-four healthy adults (mean age 22.6 years; 12 females) completed a novel decision-making task featuring alternating stable and volatile probabilistic cue contingencies while undergoing functional magnetic resonance imaging (fMRI). A hierarchical Bayesian model estimated PRI as an urgency-to-respond process, whose parameters were dynamically modulated by volatility. These model-derived indices correlated with established trait impulsivity measures, supporting their construct validity. Model-based fMRI analyses identified a distributed cortico-subcortical network including anterior insula, dorsal anterior cingulate cortex, striatum, and monoaminergic midbrain regions, whose activity tracked within-trial PRI estimates as they evolved over time. Connectivity analyses further showed that high volatility enhanced interactions between subnetworks typically associated with promoting or inhibiting impulsive action. Together, these results outline a neurocomputational account in which environmental uncertainty modulates PRI through interacting brain circuits, offering a principled framework for further probing the transdiagnostic role of impulsivity across neuropsychiatric and neuropsychopharmacological contexts.

neuroscience↗

bioRxiv2024

Putaminal dopamine modulates movement motivation in Parkinson's disease

The relative inability to produce effortful movements (akinesia) is the most specific motor sign of Parkinsons disease. The motor motivation hypothesis suggests that akinesia may not reflect a deficiency in motor control per se, but a deficiency in cost-benefit considerations for motor effort. For the first time, we investigated the quantitative effect of dopamine depletion on the motivation of motor effort in Parkinsons disease. A total of 21 patients with Parkinsons disease and 26 healthy controls were included. An incentivized force task was used to capture the amount of effort participants were willing to invest for different monetary incentive levels and dopamine transporter depletion in the bilateral putamen was assessed. Our results demonstrate that patients with Parkinsons disease applied significantly less grip force than healthy controls, especially for low incentive levels. Congruously, decrease of motor effort with greater loss of putaminal dopaminergic terminals was most pronounced for low incentive levels. This signifies that putaminal dopamine is most critical to motor effort when the trade-off with the benefit is poor. Taken together, we provide direct evidence that the reduction of effortful movements in Parkinsons disease depends on motivation and that this effect is associated with putaminal dopaminergic degeneration.

neuroscience↗

bioRxiv2024

Bayesian Workflow for Generative Modeling in Computational Psychiatry

Computational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been suggested which, however, has rarely been applied in Translational Neuromodeling and Computational Psychiatry (TN/CP) so far. Here, we present a worked example of Bayesian workflow in the context of a typical application scenario for TN/CP. This application example uses Hierarchical Gaussian Filter (HGF) models, a family of computational models for hierarchical Bayesian belief updating. When equipped with a suitable response model, HGF models can be fit to behavioural data from cognitive tasks; these data frequently consist of binary responses and are typically univariate. This poses challenges for statistical inference due to the limited information contained in such data. We present a novel set of response models that allow for simultaneous inference from multivariate (here: two) behavioural data types. Using both simulations and empirical data from a speed-incentivised associative reward learning (SPIRL) task, we show that harnessing information from two different data streams (binary responses and continuous response times) improves the accuracy of inference (specifically, identifiability of parameters and models). Moreover, we find a linear relationship between log-transformed response times in the SPIRL task and participants uncertainty about the outcome. Our analysis illustrates the benefits of Bayesian workflow for a typical use case in TN/CP. We argue that adopting Bayesian workflow for generative modelling helps increase the transparency and robustness of results, which in turn is of fundamental importance for the long-term success of TN/CP.

neuroscience↗

bioRxiv2023

Preserved striatal innervation and motor function despite severe loss of nigral dopamine neurons following mitochondrial dysfunction induced by mtDNA mutations

Degeneration of dopamine neurons in the substantia nigra and their striatal axon terminals causes cardinal motor symptoms of Parkinsons disease (PD). In idiopathic cases, high levels of mitochondrial DNA (mtDNA) mutations associated with mitochondrial dysfunction are a central feature of these vulnerable neurons. Here we present a mouse model expressing the K320E-variant of the mitochondrial helicase Twinkle in dopamine neurons, leading to accelerated mtDNA ageing. K320E-TwinkleDaN mice showed normal motor function at 20 months of age, although already [~]70% of nigral dopamine neurons had perished. The remaining neuron population still preserved [~]75% of axon terminals in the dorsal striatum, which enabled normal dopamine release. Transcriptome analysis and viral tracing confirmed compensatory axonal sprouting of surviving nigral dopamine neurons. We conclude that a small population of substantia nigra neurons can adapt to mtDNA mutations and maintain motor control in mice, holding chances for new treatment strategies in PD patients.

neuroscience↗